ArticleThe European physical journal. Special topics2022
COVID-19 disease diagnosis with light-weight CNN using modified MFCC and enhanced GFCC from human respiratory sounds.
Article in The European physical journal. Special topics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- A Novel AAF-SwinT Model for Automatic Recognition of Abnormal Goat Lung Sounds.Animals : an open access journal from MDPI · 2026Article
- Development and Validation of a Machine Learning Method Using Vocal Biomarkers for Identifying Frailty in Community-Dwelling Older Adults: Cross-Sectional Study.JMIR medical informatics · 2025Article
- Artificial intelligence-based framework to identify the abnormalities in the COVID-19 disease and other common respiratory diseases from digital stethoscope data using deep CNN.Health information science and systems · 2024Article
- Automatic Detection of Dyspnea in Real Human-Robot Interaction Scenarios.Sensors (Basel, Switzerland) · 2023Article
- Interpretation of lung disease classification with light attention connected module.Biomedical signal processing and control · 2023Article
- Coswara: A respiratory sounds and symptoms dataset for remote screening of SARS-CoV-2 infection.Scientific data · 2023Article
- Dyspnea Severity Assessment Based on Vocalization Behavior with Deep Learning on the Telephone.Sensors (Basel, Switzerland) · 2023Article
- An overview of deep learning techniques for COVID-19 detection: methods, challenges, and future works.Multimedia systems · 2023Article
- COVID-19 Detection from Chest X-rays Using Trained Output Based Transfer Learning Approach.Neural processing letters · 2022Article
- Challenges and Opportunities of Deep Learning for Cough-Based COVID-19 Diagnosis: A Scoping Review.Diagnostics (Basel, Switzerland) · 2022Article
- COVID-19 disease diagnosis with light-weight CNN using modified MFCC and enhanced GFCC from human respiratory sounds.The European physical journal. Special topics · 2022Article
- Long-term prediction of the sporadic COVID-19 epidemics induced byThe European physical journal. Special topics · 2022Article
- COVID-19: respiratory disease diagnosis with regularized deep convolutional neural network using human respiratory sounds.The European physical journal. Special topics · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the last 2 years, medical researchers and clinical scientists have paid close attention to the problem of respiratory sound classification to classify COVID-19 disease symptoms. In the physical world, very few AI-based (Artificial Intelligence) techniques are often used to detect COVID-19/SARS-CoV-2 respiratory disease symptoms from the human respiratory system-generated acoustic sounds such as acoustic voice sound, breathing (inhale and exhale) sounds, and cough sound. We propose a light-weight Convolutional Neural Network (CNN) with Modified-Mel-frequency Cepstral Coefficient (M-MFCC) using different depths and kernel sizes to classify COVID-19 and other respiratory sound disease symptoms such as Asthma, Pertussis, and Bronchitis. The proposed network outperforms conventional feature extraction models and existing Deep Learning (DL) models for COVID-19/SARS-CoV-2 classification accuracy in the range of 4-10%. The model's performance is compared with the COVID-19 crowdsourced benchmark dataset and gives a competitive performance. We applied different receptive fields and depths in the proposed model to get different contextual information that should aid in classification. And our experiments suggested 1
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